Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images

Journal of Digital Imaging
Simona MoldovanuAnjan Biswas

Abstract

This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, having the sum of its weights equal to the transcendental number π value provided by the Gregory-Leibniz infinite series. It allows maintaining a lower rate of useful pixel loss. The proposed method has been tested in two ways. First, it has been validated as a binary method by comparing and contrasting with Otsu's, Sauvola's, Niblack's, and Bernsen's binary methods. Secondly, its accuracy has been verified against three state-of-the-art skull-stripping methods: the graph cuts method, the method based on Chan-Vese active contour model, and the simplex mesh and histogram analysis skull stripping. The performance of the proposed method has been assessed using the Dice scores, overlap and extra fractions, and sensitivity and specificity as statistical methods. The gold standard has been provided by two neurologist experts. The proposed method has been tested and validated on 26 image series which contain 216 images from two publicly avai...Continue Reading

References

Dec 31, 2003·Academic Radiology·Marcel PrastawaGuido Gerig
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Nov 10, 2013·Academic Radiology·Jimit DoshiChristos Davatzikos
Mar 7, 2014·Biomedizinische Technik. Biomedical Engineering·Mirela Visan PungaLuminita Moraru

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Citations

May 31, 2017·Microscopy Research and Technique·Shouvik ChakrabortyKalyani Mali

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